Changing the parameters of an element of an imported ML model

You can change some parameters of an element of an imported ML model.

Parameters cannot be changed if the ML model is assigned the Ready for publication or Published status.

System administrators and users who have the Edit untrained models permission from the Manage ML models group of rights can edit the settings of elements of imported ML models. The functionality is available after a license key is added.

To change the parameters of an imported ML model element:

  1. In the main menu, select the Models section.
  2. In the asset tree, select the ML model element that you want to change.

    A list of options appears on the right.

  3. In the upper-right corner of the window, click the Edit button.
  4. Adjust the following element settings, if needed:
    • Name and description of the ML model element
    • Reminder period

      This parameter is unavailable for editing if the ML model is in the Historical inference in progress or Streaming inference in progress state.

      Modifying this setting changes anomaly detection sensitivity.

    • Period of recurring alert suppression

      This parameter is unavailable for editing if the ML model is in the Historical inference in progress or Streaming inference in progress state.

      Modifying this setting changes anomaly detection sensitivity.

    • Anomaly observation period

      This parameter is unavailable for editing if the ML model is in the Historical inference in progress or Streaming inference in progress state.

      Modifying this setting changes anomaly detection sensitivity.

    • Anomaly duration share in interval

      This parameter is unavailable for editing if the ML model is in the Historical inference in progress or Streaming inference in progress state.

      Modifying this setting changes anomaly detection sensitivity.

    • Color of incident dot indicators
    • Incident status and cause
    • Detection threshold

      This parameter is unavailable for editing if the ML model is in the Historical inference in progress or Streaming inference in progress state.

      The detection threshold value was set after training an element of the imported ML model. Modifying this setting changes anomaly detection sensitivity.

    • Expert opinion
  5. In the upper-right corner of the window, click the Save button.

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